AI infrastructure costs can spiral without visibility. Token budgets, per-key spend caps, and real-time alerts give engineering and finance teams the levers they need to keep LLM costs predictable.
LLM billing is fundamentally different from traditional API pricing. A REST call to a weather API costs the same every time. An LLM call costs proportionally to the length of the prompt and the response — and both are determined at runtime by user input and model behaviour, not by you.
Add multiple teams, multiple models, and a product that surfaces AI to end users, and monthly costs become unpredictable. A single poorly-written prompt that sends an entire database record to a model can cost 50× more than intended. A runaway loop in a background job can exhaust a monthly budget in hours.
Providers charge for input tokens and output tokens separately. Input tokens include your system prompt, conversation history, and user message. Output tokens are the model's response. Prices vary significantly:
System prompts that repeat on every call are a common cost leak. A 2,000-token system prompt sent 100,000 times per month costs €200–3,000 depending on the model — before a single word of user input.
Intellixer gives each API key a configurable monthly spend cap. When a key's cumulative spend approaches the cap, the platform sends an email alert at 80% and hard-stops calls at 100%. This prevents runaway costs at the key level without requiring application code changes.
Intellixer's token packages start at €10 and include full spend visibility, per-key caps, and email alerts out of the box. No configuration required.